Channel
@agathalawyer
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
104subscribers
+58 since we began measuring on 25 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003968885840 |
|---|---|
| Type | Channel |
| Username | @agathalawyer |
| Created | 15 July 2026 — measured — dated from the channel’s first post |
| First recorded | 25 August 2026 |
| Last confirmed live | 17 September 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 17 September 2026 |
| On Telegram | t.me/agathalawyer |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Sept 2026, 12:58 | 104 | +1 |
| 10 Sept 2026, 01:00 | 103 | +6 |
| 1 Sept 2026, 06:15 | 97 | +51 |
| 26 Aug 2026, 00:13 | 46 | no change |
| 25 Aug 2026, 22:00 | 46 | first reading |
7 posts held, back to 15 July 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
| Window | Rolling 30 days · latest post in window 25 August 2026 |
|---|---|
| Posts held | 7 (15 July 2026 – 25 August 2026) |
| Views total | 193 |
| Reactions total | 10 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 25 Aug 2026, 22:00 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
15 reactions across 4 posts, in 5 distinct kinds. The most used accounts for 46.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 7 | 46.7% | |
| ❤ | 3 | 20.0% | |
| 👍 | 3 | 20.0% | |
| ❤🔥 | 1 | 6.67% | |
| 🤔 | 1 | 6.67% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 4 of the 7 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 15 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 7 most recent posts we hold, published 15 July 2026 to 25 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
⭐️Новая Агата уже здесь — наш самый большой релиз Юристы неделями разбирают массивы дел вручную, прежде чем заняться работой над позицией своего доверителя. Мы подготовили большой релиз Агаты, который помогает сократить рутину до часов — и высвобождает время на то, ради чего юрист и нужен. Что появилось: 🔵 Улучшенный чат по делу. Ответ со ссылкой на конкретный документ или цитату. Что не подтверждено материалами д…
🔥7👍2❤🔥1
Legora запустила «операционную систему» для юристов — и это сигнал для России Пока российский рынок спорит об ассистентах, за рубежом Legal AI перешёл на следующий архитектурный уровень — агентную оркестрацию. Шведский стартап Legora представила Legora aOS — агентную «операционную систему», которая централизует и координирует ИИ-агентов под отдельные задачи юриста. Компания приобрела сервис регуляторного мониторинг…
❤2👍1
Юристы уже выбрали ИИ. Спойлер – чаще зарубежный, чем российский Массовое использование нейросетей юристами в России — свершившийся факт. Вопрос теперь в том, какими инструментами они пользуются. По данным опросов профессионального сообщества, генеративный ИИ вошёл в ежедневную практику: 🔵23,4% юристов используют ChatGPT 🔵21,1% — DeepSeek 🔵10,7% — Gemini Российские решения — YandexGPT и GigaChat/GigaSber — набира…
🤔1
Про Агату вышел совместный пресс-релиз — с нашим партнёром Cloud.ru. Кратко: мы перевели инференс языковых моделей Агаты на облачную инфраструктуру Cloud.ru — на сервис Evolution ML Inference. За обработку отвечают Mistral (анализ документов и извлечение сущностей) и Gemma (поиск, суммаризация, ответы пользователю). Бизнес-логика и интерфейс — на Evolution Compute. 😝 Ранее подключение дополнительных GPU занимало 1–…
❤1
Знакомьтесь: Агата Юристы любят повторять, что их работа — это стратегия, позиция, тонкая аргументация. Но если честно посмотреть, на что уходит время, картина выходит менее романтичная. Значительная часть рабочих часов тратится не на само право, а на разбор хаоса вокруг него: собрать материалы дела, понять суть, свести реквизиты, найти нужный документ в папке на 500 страниц. Мы создали Агату, чтобы облегчить имен…
Привет! Это команда Агаты Рынок юридического ИИ в России сейчас на том этапе, когда всё меняется каждый месяц: одни решения появляются, другие тихо исчезают, регулирование догоняет технологии, а юристы на местах пытаются понять — что из этого рабочий инструмент, а что красивая обёртка. Разобраться в одиночку тяжело. Поэтому мы решили завести собственное бренд-медиа — чтобы говорить про Legal Tech в России и разбират…
Channel created
Showing the 7 most recent of 7 posts we hold for @agathalawyer. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Named by 6 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 17 September 2026 — this entry's latest reading, not the date you are reading this.
“Агата в деле” (@agathalawyer), 104 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/agathalawyer.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.